Data quality and confirmatory factor analysis of the Danish EUROPEP questionnaire on patient evaluation of general practice

Abstract

Objective. The Danish version of the 23-item EUROPEP questionnaire measuring patient evaluation of general practice has not been evaluated with regard to psychometric properties. This study aimed to assess data quality and internal consistency and to validate the proposed factorial structure. Setting. General practice in Denmark. Subjects. A total of 703 general practitioners (GPs). Some 83 480 questionnaires were distributed to consecutive patients aged 18 or more attending practice during the daytime. A total of 56 594 eligible patients responded (67.8%). Main outcome measures. Data quality (mean, median, item response, missing, floor and ceiling effects), internal consistency (Cronbach's alpha and average inter-item correlation), item-rest correlations. Model fit from confirmatory factor analysis (CFA). Results. The distribution was skewed to the left for almost all items with a small floor effect (0.1–9.3%) and a ceiling effect larger than 15% (18.6–56.3%). Item response was high. For seven items “not applicable/relevant” represented more than 10% of the answers. Internal consistency was good. Item-rest correlations were below 0.60 for three items, and four items had lower correlations with their own domain than with other domains. CFA showed that four domains were highly correlated and that model fit was good for two indices (TLI and SRMR), acceptable for one index (CFI), and poor for three indices (chi-squared, RMSEA and WRMR). Conclusions. This study revealed high ceiling effects, a few items with low item-rest correlation and low item discriminant validity, and an uncertain model fit. There seems to be a need for developing response categories to bring down the ceiling effect and it is also unclear how to use the proposed domains. Future research should focus on evaluating the factorial structure when ceiling effect has been lowered, on whether items should be deleted, and on assessing the unidimensionality of each domain.

• Denmark
• factor analysis
• family practice
• patient evaluation
• questionnaires